Fig. 6: Prediction of viral aerosol interception effect of MV@GEL in human digital nasal cavity by using computational fluid dynamics-discrete particle simulation (CFD-DPS).

a Representative CT images of the human nasal cavity and its corresponding reconstructed 3D digital model. b Schematic diagram of the charge interaction between MV@GEL and aerosols in the nasal cavity during simulation calculation. Each tiny part on the nasal wall could generate a tiny Coulomb force to the specific viral aerosol. Meanwhile, the drag force of fluid, buoyancy, and gravity were considered, and the vector sum was the resultant force it received. c Distribution of inhaled viral aerosols (blue dot) at different time points (0.3 s, 0.6 s, 0.9 s, 1.2 s, and 1.5 s) of unprotection situation (upper) or MV@GEL situation (lower) after the beginning of inhalation (left), and the corresponding percentage of viral aerosols that retained in the nasal cavity or flowed into trachea at 1.5 s (right). d Flow field state of inhalation airflow (left) and the distribution of inhaled viral aerosols (blue dot) in different cross sections under unprotection situation or MV@GEL situation after 1.5 s inhalation (right). e Flow field state of exhalation airflow (left), the distribution of viral aerosols at 2.1 s (1.5 s inhalation followed by 0.6 s exhalation) under unprotection situation or MV@GEL situation (middle), accompanied with corresponding viral aerosols distribution in different cross sections (right). The inhaled viral aerosols were blue dots, and the exhalant viral aerosols were red dots.